icing prediction on blade wind turbine using forecast …...#osisoftuc #piworld ©2018 osisoft, llc...

#OSIsoftUC #PIWorld ©2018 OSIsoft, LLC


Icing prediction on blade wind turbine using forecast data

From Antoine Amossé, instrumentation and control Engineer



Summary

1. Context & Challenge

2. Data integration and algorithm

3. Results

4. Conclusion & Further development

5. Nergica



Cold climate + precipitations

Wind turbine

Icing accretion Context



Context Icing - Risks for H&S

- Fatigue on structure

- Power loss



Context

Coating Electrothermal Hot air Solution!!



Challenge

Forecast Data PI Node/Svr Model/Algorithm Action Notifications



Forecast data

- Forecast models:

HRDPS High Resolution Deterministic Prediction System

PRIVATE

NAM North American Model

PUBLIC access

+3.5 days +2 days



Forecast data

FTP site

6h

Station 1

Station 2

Station 3

Updates ~6h



Integration in PI Server

- Data is imported into PI using Universal File Loader (UFL) interface

Station 1

Station 2

Station 3

PI Server



Building structure in PI AF

Build an AF Structure to facilitate deployment of analysis and algorithms through multiple sites.

PI Server



Visualization in PI

Future Now



Building algorithm

ICING = LOW TEMP. + WATER



Building algorithm

<TEMP

0degC

>PrecipiationRate

0mm/h

Low Temp.

Water

AND Icing

ICING = LOW TEMP. + WATER



Building algorithm

Validation in PI AF



Ice measurement



Data comparison



Visualization in PI Vision



Alerting customer Choose

user/groups Manage format Edit the trigger

12h

1h



Conclusion • Alerts are sent 12h and 1h before event to users

• Challenges • Data available periodically • Building and optimize algorithm

• PI system allows to • Deployment • Archiving & validation • Review the events



Future work

• Optimization of algorithms

• Analysis of benefits in $$ or operation time

• Microgrid management based on forecast data

• Renewable production (Wind, solar)

• Storage management (battery, flywheel)

• Load estimation



Nergica Centre of Applied research that stimulate

innovation in the renewable energy



Wind Energy Conference

Carleton-sur-Mer, QC, CANADA



Optional: Click to add a takeaway you wish the audience to leave with.

Thank You

Merci

Grazie



Conference Theme & Keywords

Icing Forecast

AF structure PI Analytics

Matlab

PI_UFL

Prediction

NAM HRDPS

Cold climate

Québec

Canada

Wind Energy

Solar Energy

Notification

Blade

Wind Turbine

In-site measurement

Icing sensors

Camera system Weather

Nergica

Nergica Nergica

Solar energy

Image Analysis Precipitation

Snow

Freezing rain

Ice pellets


RESULTS CHALLENGE SOLUTION

COMPANY and GOAL

27 #OSIsoftUC #PIWorld ©2018 OSIsoft, LLC

Icing prediction for blade wind turbine using forecast data

Nergica éolien is a center of expertise that supports the development of the wind industry through research, technology transfer and technical assistance for businesses

Deicing systems installed on wind turbine blades need to be activated prior the meteorological event, in order to prevent icing accretion.

Algorithm based on forecast data are built to detect the beginning of the icing event.

Activating heating system in wind turbine keep the blade hot and avoid ice accretion, up to a given rate

Algorithms are compared with in-site instrumentations

Benefits have not been measure yet

• Integration of forecast data

• Building algorithm to detect meteorological icing

• Send notification prior the event



• Antoine Amossé

• [email protected]

• Instrumentation and Control Analyst



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icing prediction on blade wind turbine using forecast …...#osisoftuc #piworld ©2018 osisoft, llc...

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